It may not (usually) be overt, but it’s still racism

Identifying bias is not always a simple thing. Sometimes it’s easy to see as we talked about here and other times it’s not (see our post here). The 2008 election of Barack Obama led some to proclaim we were now living in a post-racial society and others to scoff at the very idea. Racial arguments come up in very unexpected places—which would lead us to think the issues simmer just under the surface. Witness a “prominent Columbia architecture professor” who “punched a female university employee in the face” during a “heated argument about race relations”.

Don’t kid yourself. The reality is that racism is thriving. It’s just different. Researchers have been talking about modern racism for a long time now as we discuss here and attempting to measure covert or ‘implicit racism’. But it’s been tough to take the research methods (the most well-known measure is the Implicit Association Test) and apply them to the real-life/real-time assessment of racial bias.

Some new research begins to move us closer to being able to assess implicit racial prejudice by using a variation on the Implicit Association Test called the Go/No-go Association Task (GNAT). The researchers used a simple and elegant means of assessing seemingly unrelated responses (don’t you love how those psychologists do that?) over a five week period in 2008 (measuring implicit racism, attitudes toward Barack Obama, and then who they voted for in the election). Then the researchers went back to the same participants again (a year later) and asked them about attitudes toward the current healthcare debate. The results were striking (and are nicely summarized here).

In brief, health-care proposals were shown to participants and randomly assigned to being either Bill Clinton’s healthcare reform plan or Barack Obama’s healthcare reform plan. Among biased respondents, support for the ‘Clinton’ plan was 70% while support for the ‘Obama’ plan was 41%. Same plan. Different Presidents. Different races. (Among non-biased respondents, support for the plan was roughly the same no matter whose plan it was said to be.)

We first saw this reality while doing pre-trial research in a plane crash case where the airline had acknowledged negligence and all that was left to determine was damages to some surviving passengers. It was shocking. This blog post is not merely a screed against racism (although we wish we could do more to end it). As we have noted numerous times, various kinds of bias play a part in virtually every case. We have the responsibility to monitor how these forces will compromise the jury’s (or even the judge’s) ability to deliver a just verdict. We are all responsible for assessing the existence of racial bias (and keeping up with what it looks like as it morphs) and sorting through how to best represent our clients in ensuring their story is heard.

(If you’d like to read the paper we wrote with recommendations for responding to racial bias, you can download it free at our website.)